{"has_next":true,"jobs":[{"id":"a6cf2026-eaea-495b-8177-860a11bedb45","company_id":"168d43fe-0922-420c-9743-59e0a899fd9d","title":"Data Scientist","slug":"data-scientist-24024c78","description":"A Career with Point72’s Technology Team\n As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications.\n As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business.\n  \n What you’ll do\n \n Lead the development and deployment of advanced models and algorithms that turn complex data into actionable insights to influence decisions across the organization\n Build and champion the rollout of a technology insights product, setting clear service standards, aligning stakeholders, and establishing transparent metrics to measure impact and drive adoption\n Design and maintain a centralized analytics platform that unifies key performance indicators, satisfaction scores, and operational metrics into intuitive dashboards for leadership\n Develop automated data pipelines and validation processes to gather, clean, and prepare large sets of structured and unstructured data for modeling and analysis\n Partner with data engineers, analysts, and business partners to translate business challenges into scalable, production-ready data solutions and shared standards\n Create reports and drill-down analyses that highlight service health, enable targeted action planning, and support proactive management\n Monitor and analyze performance across service quality, project manager satisfaction, efficiency, operational risk, and cost, highlighting trade-offs and providing strategic recommendations\n Use historical trend analysis and experimentation to uncover recurring issues, measure the impact of corrective actions, and drive continuous improvement\n Integrate third-party data sources and application programming interfaces into the analytics ecosystem to expand capabilities and enrich models\n Explore and implement modern cloud-native and distributed computing tools and methodologies to improve scalability, reliability, and reproducibility\n \n  \n What’s required\n \n 5–10 years of professional experience in data science or a closely related field in financial services or technology environments\n Bachelor's or master's degree in computer science, data science, statistics, engineering, or a related technical discipline\n Deep expertise in statistical modeling, machine learning, and data mining using Python, R, or similar programming languages\n Demonstrable experience with cloud-based analytics platforms, such as Amazon Web Services (AWS), and distributed computing frameworks, such as Spark or Databricks\n Strong skills in data wrangling, feature engineering, data quality management, and production data pipeline design\n Experience designing and implementing performance management systems, dashboards, or service excellence frameworks that inform leadership decisions\n Solid understanding of data architecture, data governance, reproducible research practices, and model monitoring in production\n Experience with version control systems—such as Git—continuous integration and delivery workflows, and modern workflow orchestration tools\n Proven ability to communicate complex analyses clearly to technical and non-technical stakeholders and to collaborate effectively in fast-paced, high-stakes environments\n Commitment to the highest ethical standards\n \n  \n We take care of our people\n We invest in our people, their careers, their health, and their well-being. When you work here, we provide:\n \n Fully-paid health care benefits\n Generous parental and family leave policies\n Volunteer opportunities\n Support for employee-led affinity groups representing women, people of color and the LGBT+ community\n Mental and physical wellness programs\n Tuition assistance\n A 401(k) savings program with an employer match and more\n \n  \n About Point72\n Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit  https://point72.com","salary_min":200000,"salary_max":300000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"principal","tags":["distributed-systems","data-pipeline","mlops","data-science"],"apply_url":"https://boards.greenhouse.io/point72/jobs/8568268002?gh_jid=8568268002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T16:17:45Z","expires_at":"2026-06-29T14:11:58.685291Z","created_at":"2026-05-30T14:11:58.799327Z","updated_at":"2026-05-30T14:11:58.799327Z","company_name":"Point72","company_slug":"point72","company_logo_url":"https://www.google.com/s2/favicons?domain=point72.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a6cf2026-eaea-495b-8177-860a11bedb45"},{"id":"31d8f599-c440-4857-a6e7-1da4b19cf92b","company_id":"654d4532-88db-435d-8a6f-161b8c5a491e","title":"Senior Manager, Data Science - Styling Algorithms","slug":"senior-manager-data-science-styling-algorithms-de952706","description":"About Stitch Fix, Inc. \n Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours.  We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.\n About the Role \n At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems.  \n We are looking for an experienced Styling Algorithms Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our styling algorithms, which empower our human stylists to delight clients by nailing their fit and style. This includes ML-, AI-, and product-driven feature curation and testing for our proprietary styling platform, as well as client-facing AI personalization experiences, such as Stitch Fix Vision, our virtual try-on.\n Responsibilities: \n \n Champion bold AI and ML interventions to improve our styling experiences, enabling our stylists to have a multiplicative impact on their client connection points.\n Likewise, actively shape the product roadmap for direct client-facing styling experiences, expanding the breadth and depth of personalization touchpoints to complement and inform our human stylists.\n Inspire your team by fostering a culture of ideation, ownership, feedback, and collaboration between team members and with cross-functional partners.\n Act as an advocate for our Styling and Merchandising teams, empowering partners to understand trends in stylist feedback and inventory surfacing algorithms for rapid action on emergent opportunities. \n Work with product managers, other data science teams, UI/UX designers, and business leaders to define and optimize against business objectives for our suite of styling experiences.\n Oversee the end-to-end algorithm development lifecycle, from ideation and experimentation to testing and deployment in a production environment.\n Identify and implement best practices for team collaboration, code quality, use of AI, and data management.\n Stay up-to-date with advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.\n \n About You \n This is what you’ll need to succeed in this role from day 1. \n Requirements: \n \n Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s or PhD preferred. \n 5+ years of experience in design and deployment of AI and ML solutions, ideally in retail personalization, with an emphasis on agentic capabilities.\n 2+ years of experience as a team technical lead or direct people manager.\n Ability to write and review production-grade code, ideally in Python.\n Applied knowledge of AI-assisted coding best practices and development of agentic product solutions.\n Excels at building trust with your team, stakeholders, and technical partners.\n Excellent communication skills with the ability to articulate complex technical concepts to business audiences.\n Experience with online A/B testing, experimentation frameworks, and performance metrics.\n Familiar with cloud-based infrastructure and distributed data systems.\n Compensation and Benefits This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site. \n Salary Range\n $200,000 — $246,000 USD \n This link leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts","salary_min":200000,"salary_max":246000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["healthcare","generative-ai","agents","payments","data-science"],"apply_url":"https://www.stitchfix.com/careers/jobs?gh_jid=7954690\u0026gh_jid=7954690","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T15:16:09Z","expires_at":"2026-06-29T14:18:30.876264Z","created_at":"2026-05-29T15:09:51.374959Z","updated_at":"2026-05-30T14:18:30.987883Z","company_name":"Stitch Fix","company_slug":"stitch-fix","company_logo_url":"https://www.google.com/s2/favicons?domain=stitchfix.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/31d8f599-c440-4857-a6e7-1da4b19cf92b"},{"id":"dc3be083-3d88-4196-ae36-689fe5f1b3fe","company_id":"654d4532-88db-435d-8a6f-161b8c5a491e","title":"Senior Manager, Data Science - Foundational Models","slug":"senior-manager-data-science-ee646aa7","description":"About Stitch Fix, Inc. \n Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours.  We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.\n  \n About the Role \n At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems.  \n We are looking for an experienced Foundational Models Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our core scoring and ranking algorithms. These industry-leading machine learning models match clients to available inventory, supporting our stylists in designing Fixes and powering online personalization directly to our clients.\n Responsibilities: \n \n Champion cutting-edge machine learning and AI techniques to improve holistic client engagement, personalization, and overall growth.\n Represent our core algorithmic capabilities in cross-functional forums, including with our executive leadership team, synthesizing business requirements and translating technical solutions with radical transparency and a solution-oriented mindset.\n Lead and inspire a team building transformative capabilities at the heart of our company’s value proposition, synthesizing and balancing multiple business objectives.\n Foster a culture of ownership for holistic business outcomes within the team, encouraging proactive engagement with cross-functional partners.\n Drive the development and optimization of our prediction and recommendation algorithms, ensuring they provide personalized, relevant, and engaging fashion recommendations for stylists and clients.\n Oversee the end-to-end algorithm development lifecycle—from ideation and experimentation to testing and deployment in a production environment.\n Manage the prioritization and execution of key algorithmic projects while balancing business needs, technical feasibility, and timelines.\n Implement industry best practices for team collaboration, code quality, use of AI, and data management.\n Stay up-to-date with the latest trends and advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.\n \n About You \n This is what you’ll need to succeed in this role from day 1. \n Requirements: \n \n Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s or PhD preferred. \n 5+ years of experience in design and deployment of machine learning algorithms, ideally in retail applications of deep learning and recommendation systems.\n 2+ years of experience in a direct people management role, with a track record of inspiring and motivating direct reports, and connecting team priorities to business objectives.\n Ability to write and review production-grade code, ideally in Python.\n Applied knowledge of AI-assisted coding best practices and development of agentic product solutions.\n Excels at building trust with your team, stakeholders, and technical partners.\n Excellent communication skills with the ability to articulate complex technical concepts to non-technical audiences.\n Experience with online A/B testing, experimentation frameworks, and performance metrics.\n Familiar with cloud-based infrastructure and distributed data systems.\n Compensation and Benefits This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site. \n Salary Range\n $200,000 — $246,000 USD \n This link leads t","salary_min":200000,"salary_max":246000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","healthcare","agents","generative-ai","payments","data-science"],"apply_url":"https://www.stitchfix.com/careers/jobs?gh_jid=7947680\u0026gh_jid=7947680","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T19:21:44Z","expires_at":"2026-06-29T14:18:30.789303Z","created_at":"2026-05-28T14:20:06.359409Z","updated_at":"2026-05-30T14:18:30.909247Z","company_name":"Stitch Fix","company_slug":"stitch-fix","company_logo_url":"https://www.google.com/s2/favicons?domain=stitchfix.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dc3be083-3d88-4196-ae36-689fe5f1b3fe"},{"id":"5e52cfc4-669e-46bb-8b87-84c11248ba64","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Analytics Engineer","slug":"analytics-engineer-97634fa3","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Analytics Engineer - Consumer Data Science \n Check out our r/RedditEng post to learn more about the team, and what we do: https://www.reddit.com/r/RedditEng/comments/1mnmf71/analytics_engineering_reddit/  \n On Reddit, people can dive into anything through experiences built around their interests, hobbies, and passions. Our mission is to empower communities and make their knowledge accessible to everyone. With over 100,000 active communities and over 120 million daily active users, it is home to the most open and authentic conversations on the internet. Reddit’s unique and differentiated product is extremely attractive to advertisers, who can reach out to and connect to our users authentically.\n We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization, focused on the Consumer domain. We are looking for someone who can work closely with Data Scientists and members of Consumer cross-functional teams (Product, Engineering, and Design) to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s product forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to improve the user experience and grow our consumer base.\n Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas.\n Reddit has a flexible workforce! If you happen to live close to one of our physical office locations, our doors are open so you can come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.\n Responsibilities: \n \n Be an Analytics Engineering leader within the Consumer organization and a key contributor and collaborator to the success of Data Science data quality, performance, reliability, and automation initiatives.\n Be the data steward for Consumer products: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for product feature tracking, user retention analysis, A/B testing, and a large number of other data-driven activities.\n Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines.\n Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability.\n Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service.\n Provide technical guidance, mentorship, coaching and/or training to data scientists and other technical partners.\n Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.\n \n Qualifications: \n \n Degree in a quantitative discipline such as statistics, operations research, computer science, applied mathematics, economics, or physics\n 4+ years of experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment.\n Strong programming proficiency in Python, SQL, Spark, Scala, etc.\n Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data.\n Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering.\n Experience in data visualization and dashboard design.\n Deep understanding of technical and functional designs for relational and MPP Databases.\n Proven track record of cross-functional execution and collaboration. Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen.\n Self-starter, ability to work independe","salary_min":164200,"salary_max":229900,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["agents","healthcare","data-pipeline","data-science"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/7958354","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T18:42:47Z","expires_at":"2026-06-29T14:08:29.565057Z","created_at":"2026-05-27T14:08:43.457817Z","updated_at":"2026-05-30T14:08:29.678303Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5e52cfc4-669e-46bb-8b87-84c11248ba64"},{"id":"a5d985bb-042b-4ab6-9059-b7941fc36fcc","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior People Data Scientist","slug":"senior-people-data-scientist-4ff4247c","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n Instacart’s People Analytics \u0026 Research (PAR) team delivers trusted insights that help leaders make better, faster decisions and create an environment where every employee can do the best work of their career. Embedded within People Services Delivery , we partner across the People org and the business to build the data infrastructure, dashboards, analytical frameworks and research that power workforce planning, organizational health, and strategic HR initiatives for all Instacart employees. In addition, our mission is to bring these insights to life through close partnerships with partner teams across Instacart. \n We’re hiring a Senior People Data Scientist (L5) to serve as an enterprise‑wide people analytics thought partner—blending data engineering, analytics, consulting, and data product ownership . You will own complex, multi‑quarter analytical workstreams, shape company‑level people metrics, and help leaders at all levels use data to make better, more equitable decisions about our workforce.\n This is a high‑visibility IC role with significant exposure to senior HR and business leaders, ideal for someone who is equally comfortable in Snowflake, extracting insights from employee data, executive‑level storytelling, and in shaping how HR and business leaders across Instacart use data at scale. \n About the Job \n \n Help to evolve the enterprise people analytics agenda across key domains (e.g., organizational health, performance, hiring), including cross functional partnerships to align metrics to Instacart’s priorities and providing insights which help solve our more complex people problems.\n Contribute to high‑stakes, enterprise‑wide projects , such as:\n \n Drivers of retention across functions\n Implementation and analysis of people surveys across Instacart\n Organizational Health and design metrics\n Engagement survey insights and action effectiveness\n Implementation of AI in analysis workflows\n \n Design and mature self‑serve people data products (dashboards, standardized views, metric layers) that scale across HR and the business—standardizing definitions, partnering with People Tech and Finance on data architecture, and driving adoption through enablement and training.\n Own Data Warehousing and Data Architecture design decisions spanning across data ingestion, ETL/ELTs through BI Tools and LLMs.\n Bring analytical rigor to enterprise People programs (e.g., performance cycles, comp reviews, workforce planning, AES) by defining success metrics, segmenting impact, and recommending changes based on evidence and HRBP‑style judgment about feasibility and change management.\n Apply and interpret advanced methods where needed , such as predictive attrition models, cohort/survival analysis, and simple causal frameworks to evaluate program effectiveness, while keeping methods transparent and explainable to HR and business audiences.\n Serve as a partner to HRBPs, People leaders, and analysts on data literacy, metric interpretation, and responsible use of HR data. Contribute meaningfully to the team’s move from ad hoc requests to thought partnership and guidance on the appropriate use of people data for decision making.\n Champion data governance, privacy, and role‑based access across Workday, Snowflake, BI tools, and Qualtrics, partnering with People Tech and vendors to ensure HR data is accurate, secure, and fit for sensitive people decisions.\n Contribute to PAR’s roadmap, operating model, and culture —refining intake and prioritization, setting bar‑raising standards for analysis and storytelling.\n \n About You \n Minimum Qualifications \n \n 5+ years of experience in analytics, data science, business intelligence, or a closely related field, with at least 2–3+ years in People Analytics / HR data (HCM, recruiting, comp, retention, DEI, engagement, or","salary_min":161000,"salary_max":170000,"location":"Remote (Canada)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","llm","nlp","data-science"],"apply_url":"https://instacart.careers/job/?gh_jid=7958122","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T16:51:46Z","expires_at":"2026-06-29T14:08:41.826643Z","created_at":"2026-05-27T14:08:55.940238Z","updated_at":"2026-05-30T14:08:41.93919Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a5d985bb-042b-4ab6-9059-b7941fc36fcc"},{"id":"17bd9f6c-5e16-4fde-b4a9-69edd1d0b893","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior People Data Scientist","slug":"senior-people-data-scientist-7d166767","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n Instacart’s People Analytics \u0026 Research (PAR) team delivers trusted insights that help leaders make better, faster decisions and create an environment where every employee can do the best work of their career. Embedded within People Services Delivery , we partner across the People org and the business to build the data infrastructure, dashboards, analytical frameworks and research that power workforce planning, organizational health, and strategic HR initiatives for all Instacart employees. In addition, our mission is to bring these insights to life through close partnerships with partner teams across Instacart. \n We’re hiring a Senior People Data Scientist (L5) to serve as an enterprise‑wide people analytics thought partner—blending data engineering, analytics, consulting, and data product ownership . You will own complex, multi‑quarter analytical workstreams, shape company‑level people metrics, and help leaders at all levels use data to make better, more equitable decisions about our workforce.\n This is a high‑visibility IC role with significant exposure to senior HR and business leaders, ideal for someone who is equally comfortable in Snowflake, extracting insights from employee data, executive‑level storytelling, and in shaping how HR and business leaders across Instacart use data at scale. \n About the Job \n \n Help to evolve the enterprise people analytics agenda across key domains (e.g., organizational health, performance, hiring), including cross functional partnerships to align metrics to Instacart’s priorities and providing insights which help solve our more complex people problems.\n Contribute to high‑stakes, enterprise‑wide projects , such as:\n \n Drivers of retention across functions\n Implementation and analysis of people surveys across Instacart\n Organizational Health and design metrics\n Engagement survey insights and action effectiveness\n Implementation of AI in analysis workflows\n \n Design and mature self‑serve people data products (dashboards, standardized views, metric layers) that scale across HR and the business—standardizing definitions, partnering with People Tech and Finance on data architecture, and driving adoption through enablement and training.\n Own Data Warehousing and Data Architecture design decisions spanning across data ingestion, ETL/ELTs through BI Tools and LLMs.\n Bring analytical rigor to enterprise People programs (e.g., performance cycles, comp reviews, workforce planning, AES) by defining success metrics, segmenting impact, and recommending changes based on evidence and HRBP‑style judgment about feasibility and change management.\n Apply and interpret advanced methods where needed , such as predictive attrition models, cohort/survival analysis, and simple causal frameworks to evaluate program effectiveness, while keeping methods transparent and explainable to HR and business audiences.\n Serve as a partner to HRBPs, People leaders, and analysts on data literacy, metric interpretation, and responsible use of HR data. Contribute meaningfully to the team’s move from ad hoc requests to thought partnership and guidance on the appropriate use of people data for decision making.\n Champion data governance, privacy, and role‑based access across Workday, Snowflake, BI tools, and Qualtrics, partnering with People Tech and vendors to ensure HR data is accurate, secure, and fit for sensitive people decisions.\n Contribute to PAR’s roadmap, operating model, and culture —refining intake and prioritization, setting bar‑raising standards for analysis and storytelling.\n \n About You \n Minimum Qualifications \n \n 5+ years of experience in analytics, data science, business intelligence, or a closely related field, with at least 2–3+ years in People Analytics / HR data (HCM, recruiting, comp, retention, DEI, engagement, or","salary_min":161000,"salary_max":170000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["nlp","llm","data-pipeline","data-science"],"apply_url":"https://instacart.careers/job/?gh_jid=7958121","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T16:49:45Z","expires_at":"2026-06-29T14:08:41.750936Z","created_at":"2026-05-27T14:08:56.031655Z","updated_at":"2026-05-30T14:08:41.861595Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/17bd9f6c-5e16-4fde-b4a9-69edd1d0b893"},{"id":"1598afd6-7ff3-417e-b3a0-138ecb576a46","company_id":"b467c425-56b3-40ce-826a-e603e82a08bd","title":"Machine Learning Scientist","slug":"machine-learning-scientist-de3cf41b","description":"Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.  \n At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.  \n A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. \n WHY DATA SCIENCE AND ANALYTICS \n The Data Science \u0026 Analytics organization's mission is to increase our speed, frequency, and acumen in making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products, and measure impact on our community of players and developers.\n In Data Science \u0026 Analytics, you will contribute to horizontal ML systems and infrastructure that enable us to understand the trajectory of users and creators as well as the overall business to inform investment opportunities and accelerate our growth. These systems inform experiment decision making, product roadmaps, and execution risk on our road to connecting one billion users. \n You Will:  \n \n Develop, build, and support large scale forecasting systems for business growth\n Develop, build, and support modeling of long-term user outcomes\n Design and implement batch prediction infrastructure that ensures high-levels of accuracy, provides explainability, and quantifies uncertainty\n Collaborate with data science and product partners to unlock causal understanding of our business growth and to develop scalable solution for measuring ecosystem health\n Model and promote a high bar for technical excellence in the broader data science and ML community.\n Communicate strategic findings to influence company and team-level roadmaps\n Partner with Data Engineering and Data Platform teams to ensure model development, reporting, and monitoring systems are built in a reliable and robust way. \n \n You Have:  \n \n 5+ years of industry experience in prototyping and building scalable machine learning solutions.\n Experience building scalable and robust ETL data and ML pipelines with complex upstream dependencies and accountability for downstream consumers\n Experience with time series modeling in practice and theory. Experience with foundational time series models (i.e. transformer based) and fine tuning frameworks.\n Demonstrated ability to lead project areas from scratch, and break product requirements into iterative deliverable stages.\n Strong communication skills to connect model outputs to company-level strategy and to integrate horizontal solutions into vertical team operations and systems.\n An Advanced Degree (MSc or PhD) or equivalent degree in Statistics, Economics, Operations Research, Computer Science, Applied Math, Physics, Engineering, or other quantitative fields.\n For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page .\n Annual Salary Range\n $263,670 — $322,820 USD \n Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).\n Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.\n For US based roles only, please note the Company may not be able to employ candidates for this role who have United","salary_min":263670,"salary_max":322820,"location":"San Mateo, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","data-pipeline","machine-learning","data-science"],"apply_url":"https://careers.roblox.com/jobs/7950872?gh_jid=7950872","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-22T03:02:22Z","expires_at":"2026-06-29T14:17:02.317307Z","created_at":"2026-05-27T14:17:50.446567Z","updated_at":"2026-05-30T14:17:02.42643Z","company_name":"Roblox","company_slug":"roblox","company_logo_url":"https://www.google.com/s2/favicons?domain=roblox.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1598afd6-7ff3-417e-b3a0-138ecb576a46"},{"id":"30691bcd-dc37-4149-9f33-16fd4c446705","company_id":"74257563-5513-4a8d-a0f7-01f00c59aed6","title":"Senior Data Scientist, Guest Travel Insurance (Algorithms)","slug":"senior-data-scientist-guest-travel-insurance-algorithms-d5dcd08e","description":"Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. \n The Community You Will Join: \n Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. Travel should feel safe—and AirCover is how we deliver on that promise. Through Guest Travel Insurance (GTI), we offer guests peace of mind at the moment of booking and throughout their trip. As a Data Scientist on AirCover, you’ll work at the intersection of insurance, personalization, and machine learning—building intelligent systems that help the right guest discover the right coverage at the right moment. You’ll join a tight-knit, high-output DS team that runs one of Airbnb’s most experiment-dense personalization roadmaps, partnering daily with product, engineering, operations, and legal to ship work that directly affects guest trust and revenue.\n The Difference You Will Make: \n We’re looking for a machine learning expert who is excited to own hard problems end-to-end—from prototype to production. You’ll have direct scope to contribute and lead across:\n \n Package personalization \u0026 ML-based recommendation: Evolve rule-based guest segmentation into a full ML recommendation system that surfaces the right insurance (e.g., trip cancellation, accidental damage coverage, on-trip protection) to each guest based on purchase intent, trip attributes, listing signals, and user history.\n Content personalization: Build models that rank and select benefit messaging for each guest—deciding which coverages to highlight, in what order, and with what framing—drawing on learnings from segmentation experiments and LLM-assisted content prototyping.\n Intent modeling: Develop and productionize ML models (from gradient-boosted trees to deep learning) that predict a guest’s likelihood to value specific coverages, using structured booking data and unstructured signals.\n Journey understanding and optimization: Leverage reinforcement learning to personalize across user journey, with understanding on user preferences on entry point, price, notification frequency, and trip characteristics\n High-velocity experimentation: Design and run adaptive experiments to maximize learning within tight traffic constraints; sequence ERFs strategically to keep the personalization roadmap moving.\n \n A Typical Day: \n \n Dig into experiment results to surface high-impact personalization opportunities; translate what you find into crisp scientific problem formulations that balance rigor with speed-to-learning.\n Work closely with product managers, engineers, operations, legal, and privacy partners to align on ML requirements, de-risk design decisions, and gather requirements on explainability and compliance.\n Hands-on develop, evaluate, and ship ML models and data pipelines at scale—batch and real-time, structured and unstructured—using Airbnb’s paved-path tooling and AI native mindset\n Prototype and iterate quickly: turn a new idea into a working model in a prototype, get early signals from an experiment, then productionize what works. You move fast and don’t wait to be asked.\n Present findings and proposals at team reviews and to technical, product, and executive stakeholders—making complex ML results legible without dumbing them down, and generating conviction on the roadmap ahead.\n Stay current with the research community; draw on state-of-the-art advances in recommendation systems, LLMs, and personalization to raise the bar for what the team ships. Occasionally publish externally or present at conferences to advance Airbnb’s scientific standing.\n \n Your Expertise: \n \n 5+ years of relevant industry experience (e.g., ML scientist, tech lead, junior faculty) and a Master’s degree or PhD with 2+ yrs in a relevant field.\n Proven hands-on experience building and shipping personalization and recommendation systems at scale: strong intuition for feature engineering, user modeling, and the full ML lifecycle (training, serving, monitoring, iteration). Experience with LLMs, Computer Vision or content-understanding topics is a strong plus.\n Strong fluency in Python and SQL; hands-on experience with TensorFlow or PyTorch, Airflow, and a data warehouse environment.\n Deep understanding of ML algorithms (gradient-boosted trees, deep learning, optimization) and experiment design—including A/B testing, multi-armed bandits, and the practical constraints of running experiments at scale. Causal inference skills are a plus.\n Exceptional communicator: you can make complex ML work legible to engineers, product managers, legal, and executives alike— written and verbal. You treat communication as a core part of the job, not an afterthought.\n Self","salary_min":179000,"salary_max":210000,"location":"United States","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["tensorflow","llm","deep-learning","pytorch","data-pipeline","computer-vision","reinforcement-learning","data-science"],"apply_url":"https://careers.airbnb.com/positions/7926614?gh_jid=7926614","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-21T15:55:19Z","expires_at":"2026-06-29T14:09:02.248406Z","created_at":"2026-05-27T14:09:19.322462Z","updated_at":"2026-05-30T14:09:02.357735Z","company_name":"Airbnb","company_slug":"airbnb","company_logo_url":"https://www.google.com/s2/favicons?domain=airbnb.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/30691bcd-dc37-4149-9f33-16fd4c446705"},{"id":"80a16f64-3898-471c-b738-ec10c5b80e95","company_id":"fa25a1f6-acd0-42b6-a229-f4d258ed5c3d","title":"Staff Data Scientist","slug":"staff-data-scientist-b14f8c95","description":"Employee Applicant Privacy Notice \n Who we are: \n \n Shape a brighter financial future with us.\n Together with our members, we’re changing the way people think about and interact with personal finance.\n We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. \n Social Finance, LLC seeks Staff Data Scientist in San Francisco, CA: \n Job Duties: Identify high impact business opportunities to help members achieve their financial goals. Mentor and guide data scientists in the team by promoting best practices, strong technical decisions, coding standards, and thorough documentation. Develop and apply machine learning models to solve business problems. Evaluate and interpret the results of data analysis. Build strong relationships with stakeholders and present insights on a regular cadence communicating findings to both technical and nontechnical stakeholders. Design and implement data collection. Build data pipelines to deploy production level datasets. Collaborate with cross functional teams and business leader to understand needs and offer data driven solutions. Participate in internal team Knowledge sharing session and willingness to mentor junior Data Scientists in the team. Part time telecommuting is an option. Hybrid work from Sofi offices in San Francisco, CA. \n Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and three (3) years of experience in the job offered or related occupation.\n Special Skill Requirements: (1.) Artificial Intelligence (AI) \u0026 Machine Learning (ML); (2.) Natural Language Processing (NLP); (3.) Time Series Forecasting; (4.) ETL Pipelines; (5.) AWS (Sagemaker, S3, EMR); (6.) Advanced clustering; (7.) Data Visualization; (8.) A/B testing; (9.) Collaboration with cross-functional partners; (10.) Leadership. Any suitable combination of education, training and/or experience is acceptable. Part time telecommuting is an option. Hybrid work from Sofi offices in San Francisco, CA. \n Salary: $250,080.00 - $275,088.00 per year. \n Submit resume with references using the apply button on this posting or by email to: Req.# 1014.323.2 at: ATTN: HR, jobadverts@sofi.org .\n  \n  \n #LI-DNI\n Compensation and Benefits \n The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. \n  \n To view all of our comprehensive and competitive benefits, visit our  Benefits at SoFi   page!\n SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. \n The Company hires the best qualified candidate for the job, without regard to protected characteristics. \n Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. \n New York applicants: Notice of Employee Rights \n SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. \n Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time. \n Internal Employees \n If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.","salary_min":250080,"salary_max":275088,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","nlp","cloud","data-science"],"apply_url":"https://sofi.com/careers/job/7741762003?gh_jid=7741762003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-20T16:28:47Z","expires_at":"2026-06-29T14:18:03.632869Z","created_at":"2026-05-27T14:18:55.187577Z","updated_at":"2026-05-30T14:18:03.744148Z","company_name":"SoFi","company_slug":"sofi","company_logo_url":"https://www.google.com/s2/favicons?domain=sofi.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/80a16f64-3898-471c-b738-ec10c5b80e95"},{"id":"dc48f5cd-f50e-4e92-b889-65f6a5aca36e","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Staff Data Scientist, Safety Insights","slug":"staff-data-scientist-safety-insights-1645a696","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City \u0026 Chicago) our doors are open for you to come into the office as often as you'd like.\n Reddit is poised to innovate and grow like never before, and user safety is a critical accelerant of that growth. The  Safety org is Reddit’s central Trust \u0026 Safety organization whose mission is to protect good users from bad experiences by stopping harmful content and behaviors across the site. We are looking for a Staff Data Scientist to join our Safety Insights Data Science team. In this role, you will partner closely with Safety Product, Engineering, and Machine Learning teams along with fellow Safety data scientists, to shape strategy, product development, define and evolve safety metrics, and drive analytics for some of the most important decisions in the Safety org. You will lead efforts to shape the measurement strategy for user safety, establish frameworks to quantify and monitor safety experiences, and evaluate the impact of interventions designed to protect Reddit’s communities. You will identify and prioritize opportunities for innovation, using rigorous analyses to size the potential impact of new initiatives and help the organization focus on the highest ROI areas to improve the safety experience at scale. Your work will guide decision-making and shape the strategic direction of Reddit’s safety efforts, ensuring that user safety remains a cornerstone of Reddit’s growth. \n The Safety org is one of Reddit’s largest divisions. Safety Insights works horizontally across it to provide scientific insight for product development, scaled abuse detection and mitigation, threat intelligence, and safety operations. We think big to innovate, unravel hard problems that cut across safety domains, and guide product development to protect our users from bad experiences while supporting Reddit’s long-term health and growth. \n Reddit has a remote-friendly work environment. If you live near one of our physical offices, our doors are open for you to come in as often as you’d like. Don’t live near an office? You can apply to work remotely from anywhere in the United States.\n Responsibilities: \n \n Lead the measurement strategy for user safety by defining metrics, frameworks, and dashboards that quantify and monitor safety experiences across Reddit.\n Use data and science-backed methods to inform the strategic direction of Safety product development and to rigorously assess the impact of product launches and policy or enforcement changes.\n Design and execute experiments and quasi-experimental / inferential causal analyses (e.g., difference-in-differences, synthetic controls, matching) to estimate the impact and ROI of safety initiatives, and use these results for opportunity sizing and prioritization.\n Own the design, development, and maintenance of scalable models and prototypes leveraging statistical, machine learning, or GenAI methodologies to improve Reddit safety.\n Tactically support product development and go-to-market, from problem framing and exploratory analysis through to experimentation, launch evaluation, and post-launch monitoring.\n Stay current on advances in ML, LLMs, and related methods, and evaluate where they can meaningfully improve abuse detection, risk identification, and enforcement workflows.\n Translate complex analyses into clear narratives and recommendations for stakeholders, acting as a data storyteller who can influence decisions at all levels of the Safety and Moderation orgs.\n Mentor and up-level junior Data Scientists and Analysts in technical approaches for detecting and mitigating abuse, fostering a culture of rigor and curiosity.\n \n Required Qualifications: \n \n Relevant experiences in Data Science, Applied Science, or Economist roles, preferably for safety, enforcement engineering, fraud etc.\n Ph.D. or M.S. degree in Statistics, Economics, Computer Science, Applied Mathematics or other quantitative fields (If M.S., a minimum of 8+ years of industry data science experience required; If PhD degree, a minimum of 4+ years of industry data science experience required)\n Fluent with statistical analysis, programming languages (e.g., Python) and SQL.\n Comfortable in innovative and fast-paced environments, and an innate ability to bias toward action\n Strong technical communication and demonstrated ability","salary_min":217000,"salary_max":303900,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","llm","generative-ai","healthcare","data-science"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/7863304","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-20T00:16:42Z","expires_at":"2026-06-29T14:08:32.132167Z","created_at":"2026-05-27T14:08:46.093885Z","updated_at":"2026-05-30T14:08:32.245481Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dc48f5cd-f50e-4e92-b889-65f6a5aca36e"},{"id":"4dbf93be-05aa-4e04-9e99-1e7793a74816","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Sr. Data Scientist, GenAI \u0026 Labeling Platforms","slug":"sr-data-scientist-genai-labeling-platforms-e43ce988","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest brings millions of people the inspiration to create a life they love. Advancements in Generative AI have opened up a wealth of opportunities for improvements in productivity and labeling quality, and we've only scratched the surface of its capabilities. Early results show strong promise for LLM-assisted labeling — reducing time and cost, focusing human rater efforts on higher-value problems, and improving the accuracy of our learnings.\n  \n This role focuses on advancing the science and systems behind labeling, evaluation, and GenAI-enabled workflows. The work spans LLM-assisted labeling, human-in-the-loop quality systems, prompt and rubric design, model evaluation, and methods for improving the speed, consistency, and usefulness of judgment-based data.\n  \n We're looking for a strong senior individual contributor to execute high-impact technical work in this space, partner cross-functionally to turn successful ideas into durable platform capabilities, and grow with the team as the space evolves.\n  \n What you’ll do: \n We are looking for an experienced and highly capable Data Scientist to help us drive step function improvements in our data labeling capabilities at Pinterest. In this role, you will:\n \n Execute high-impact scientific work across GenAI-powered labeling and evaluation systems\n Identify opportunities where LLMs and related methods can improve quality, speed, coverage, and cost efficiency\n Develop prototypes that demonstrate value in areas such as prompt optimization, task decomposition, quality estimation, routing, and human-in-the-loop workflows\n Design experiments and measurement frameworks to evaluate model performance, workflow outcomes, and operational tradeoffs\n Partner with engineering, product, and data science teams to productionize successful approaches\n Apply standards for trustworthiness, including bias measurement, calibration, quality control, and responsible oversight\n Contribute to reusable methods and frameworks that can scale across teams and use cases\n Support more junior scientists and contribute to the technical health of the team\n \n  \n What we’re looking for: \n \n 6+ years of combined post-graduate academic and industry experience (or PhD + 3 years) applying scientific methods to real-world problems on large-scale data\n Strong hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems\n Experience applying LLMs or other generative AI techniques to practical workflows, systems, or products\n Ability to turn ambiguous problems into rigorous analyses, experiments, and prototypes\n Track record of writing high-quality code and using technical work to influence product or platform direction\n Solid cross-functional collaboration skills and experience working effectively across teams\n Business and product sense with the ability to define meaningful success metrics\n Self-directed learning mindset and comfort working in a rapidly evolving technical landscape\n Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred\n \n  \n Relocation Statement: \n \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. \n \n  \n In-Office Requirement Statement: \n \n \n This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. \n This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.\n \n  \n #LI-NM4\n #LI-REMOTE\n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparen","salary_min":139764,"salary_max":287749,"location":"San Francisco, CA","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["llm","generative-ai","data-engineering","data-science"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7923203","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T18:22:15Z","expires_at":"2026-06-29T14:08:27.096244Z","created_at":"2026-05-27T14:08:40.655054Z","updated_at":"2026-05-30T14:08:27.209786Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4dbf93be-05aa-4e04-9e99-1e7793a74816"},{"id":"df1eb663-3291-469f-99fa-889a704b06f9","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Data Scientist II, Infrastructure","slug":"data-scientist-ii-infrastructure-76c04719","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business.\n  \n We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical frameworks that enable Pinterest to optimize core technical systems and make better product and infrastructure decisions. \n What you’ll do: \n In this role, you will partner closely with engineering and cross-functional teams to improve how Pinterest measures, understands, and optimizes its infrastructure:\n \n Partner with engineering teams to define, measure, and improve the health, quality, and efficiency of Pinterest’s infrastructure systems.\n Build and refine metrics, dashboards, and analytical frameworks that make complex technical systems more understandable and actionable.\n Strengthen data foundations by improving metric definitions, auditing data quality, and contributing to pipeline and measurement improvements where needed.\n Design and analyze experiments, investigations, and deep dives to quantify the impact of infrastructure changes on user experience, reliability, and business outcomes.\n Translate ambiguous technical problems into clear analyses and actionable recommendations for engineering and platform partners.\n Support high-priority investigations and decision-making related to infrastructure performance, reliability, cost, and measurement quality.\n Identify opportunities to improve how Pinterest measures and optimizes infrastructure across a range of domains, such as performance, shopping infrastructure, governance, metrics quality, and site reliability. \n \n What we’re looking for: \n \n Masters degree in a relevant field such as Statistics, Applied Math, Biostatistics, or equivalent experience.\n Strong SQL and analytical programming skills, with experience working through messy, imperfect data and building reliable metrics and datasets.\n Experience partnering on or contributing to production-ready data pipelines, measurement systems, or foundational data work that improves data quality and usability.\n Solid foundation in experimentation and measurement, with the ability to design analyses, interpret results rigorously, and partner effectively with engineers and other cross-functional stakeholders.\n Demonstrated ability to translate ambiguous problems into clear analytical workstreams and actionable recommendations.\n Strong cross-functional communication skills, with the ability to explain technical findings clearly to engineering, product, and platform stakeholders.\n Ability to operate independently, prioritize across both longer-term projects and fast-turn inbound requests, and drive work forward in a dynamic environment.\n Curiosity and a builder mindset, with excitement for improving messy systems and creating more scalable, trustworthy measurement foundations.\n \n  \n Relocation Statement: \n \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. \n \n  \n In-Office Requirement Statement: \n \n This position is not eligible for relocation assistance. Visit our PinFlex page to l","salary_min":114297,"salary_max":235319,"location":"San Francisco, CA","workplace":"remote","job_type":"full-time","experience_level":"mid","tags":["data-pipeline","data-science","data-engineering","infrastructure"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7816424","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T18:21:18Z","expires_at":"2026-06-29T14:08:25.367154Z","created_at":"2026-05-27T14:08:38.877001Z","updated_at":"2026-05-30T14:08:25.481605Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/df1eb663-3291-469f-99fa-889a704b06f9"},{"id":"0f43a6be-0741-404f-b92b-b2a290da9fb5","company_id":"5799e1f6-0be1-420d-b492-b1eb8717dd2a","title":"Data Scientist, ML (Agentic, CX)","slug":"data-scientist-ml-agentic-cx-01f915e3","description":"Join us in building the future of finance.\n Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.\n About the team + role \n We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.\n The Platforms Data Science team sits at the intersection of customer experience and trust, building the intelligence that powers how Robinhood supports its customers. The team develops systems that safeguards customers and the platform while making every interaction smarter: from the in-app AI assistant that helps customers research, trade, and manage their portfolios, to the AI-powered support chatbot that resolves issues autonomously, to the machine learning systems that detect and prevent fraud and abuse in real time. These systems rely on evaluation frameworks and guardrails that maintain reliability and safety across the platform. You will work with product engineering, product management, and ML infrastructure teams to deliver production-ready AI systems at scale. Join a team where your work directly shapes how customers interact with Robinhood!\n As a Data Scientist, Agentic (CX), you will lead machine learning development across the customer experience stack. This includes models and prompts that power multi-agent orchestration, evaluation pipelines that measure model quality at scale, and personalization systems that determine when and how to engage customers. You will partner closely with product and engineering to improve reasoning, expand tool usage, and strengthen feedback loops between live systems and offline evaluation. The role offers ownership from experimentation through deployment, with opportunities to apply advanced AI techniques in a regulated environment!                                \n This role is based in our Menlo Park, CA and New York, NY offices, with in-person attendance expected at least 3 days per week. \n At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. \n What you’ll do \n \n Build and deploy machine learning models for customer support systems, including intent classification, escalation detection, clarification, summarization, and multi-agent orchestration\n Design evaluation frameworks using LLM-based review methods, human feedback loops, and automated quality metrics to identify regressions before customer impact\n Develop propensity, segmentation, and personalization models that support proactive outreach and tailored AI experiences\n Translate advances in agent architectures into production systems, partnering with engineering on prompt design, retrieval systems, tool use, memory, and orchestration\n Develop systems that maintain response quality and reliability at scale while working with product, engineering, legal, and compliance partners\n \n What you bring \n \n You have strong Python and SQL skills, with experience building and evaluating machine learning systems end to end\n You have experience with agent-based AI systems, including reasoning loops, tool use, memory, retrieval-augmented generation, and orchestration\n You have experience designing experiments and applying causal inference methods, including A/B testing and measurement design\n You are comfortable working through ambiguous problems and collaborating with partners across product and engineering\n \n Preferred Qualifications \n \n Experience building and evaluating agent-based systems for production use\n Experience developing recommendation, ranking, or personalization systems at scale\n Experience working on AI products in regulated industries such as financial services.\n \n What we offer \n \n Challenging, high-impact work to grow your career.\n Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.\n Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.\n Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.\n Employer-paid life \u0026 disability insurance, fertility benefits, and mental health benefits.\n Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!\n Exceptional office","salary_min":123000,"salary_max":144000,"location":"Menlo Park, CA","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["agents","rag","llm","data-science"],"apply_url":"https://boards.greenhouse.io/robinhood/jobs/7489476?t=gh_src=\u0026gh_jid=7489476","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-14T18:16:59Z","expires_at":"2026-06-29T14:08:49.924062Z","created_at":"2026-05-15T14:09:52.31821Z","updated_at":"2026-05-30T14:08:50.035497Z","company_name":"Robinhood","company_slug":"robinhood","company_logo_url":"https://www.google.com/s2/favicons?domain=robinhood.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0f43a6be-0741-404f-b92b-b2a290da9fb5"},{"id":"1371b780-b744-4e8b-a313-1e2fc01543d8","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Sr. Data Scientist, Trust and Safety","slug":"sr-data-scientist-trust-and-safety-509a3e81","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale experiences in a complicated ecosystem, ensuring they are safe, fair, and trustworthy is paramount. We are looking for a Senior Data Scientist to help lead Pinterest's Trust and Safety mandate by designing the foundations for measuring the prevalence of unsafe content across the platform.\n In this role, you will design and build sampling frameworks, complex data aggregations, and measurement methodologies to track Trust \u0026 Safety policy violations across complex, multi-component user interactions. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Trust \u0026 Safety Ops, subject matter expert teams, and Product Managers. The results of your work will directly influence platform safety metrics, policy compliance, and executive-level visibility into platform health.\n What you'll do:\n \n Design and develop ML-assisted sampling techniques, applying expertise in statistical methods to accurately measure the prevalence of unsafe content, treating complex multi-component interactions as distinct measurement units.\n Apply rigorous statistical methods, drawing on knowledge of all kinds of sampling methods and their proper statistical application for complicated use cases, to calculate prevalence rates for specific Trust \u0026 Safety policy violations (e.g., Adult content, Self-harm, Harassment, Misinformation) and to further expand and improve the prevalence measurement.\n Build large-scale data pipelines to aggregate Pinner-generated queries, system responses, and recommended Pin images into a unified format for human and ML-based safety labeling.\n Partner cross-functionally to orchestrate \"Offline\" dashboards and robust \"Online\" production workflows for continuous safety monitoring.\n Collaborate closely with Trust \u0026 Safety teams to translate written safety policies into unified LLM prompts, coordinate BPO labeling queues, and calibrate labeler decision quality\n \n What we're looking for:\n \n 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.\n Strong interest and hands-on experience in platform safety, prevalence measurement, adversarial testing, responsible data measurement, or Trust \u0026 Safety.\n Deep familiarity with the measurement challenges of a complex ecosystem, including statistical interpretation of data.\n Experience designing and calibrating measurement frameworks, managing complex logging tables (e.g., user/interaction/component data), and defining directional success metrics.\n Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with complex ML pipelines and up-sampling.\n Ability to drive ambiguous measurement projects end-to-end, overcoming unstructured policy dependencies with high ownership.\n Excellent written and verbal communication skills, with the ability to advocate for decision quality before releasing metrics to executive leadership.\n \n  \n In - Office Requirement Statement \n \n We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.\n This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.\n \n Relocation Statement \n \n This position is not eligible for relocation assistance.\n \n  \n #LI-NM4 \n At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary ran","salary_min":139764,"salary_max":287749,"location":"San Francisco, CA","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","llm","rust","data-science"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=7793344","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-13T20:47:58Z","expires_at":"2026-06-29T14:08:27.256492Z","created_at":"2026-05-14T14:09:34.44346Z","updated_at":"2026-05-30T14:08:27.370588Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1371b780-b744-4e8b-a313-1e2fc01543d8"},{"id":"4da9ddfa-63f4-410c-a728-67df360aad68","company_id":"654d4532-88db-435d-8a6f-161b8c5a491e","title":"Data Scientist - Decisions \u0026 Insights","slug":"data-scientist-decisions-insights-d97de8d3","description":"About Stitch Fix, Inc. \n Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours.  We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.\n About the Team \n Stitch Fix is redefining retail by blending the art of fashion with the science of machine learning. The Decisions \u0026 Insights team is at the heart of this innovation, utilizing experimentation and causal inference to power personal style. We foster a culture of ownership where Data Scientists manage the full lifecycle of their work – from initial research to model development – combining best-in-class algorithms with expert human judgment. In our data-rich environment, your work will directly influence how millions of clients discover what they love, driving the company’s bottom line through technical excellence.\n Consisting of data scientists from diverse backgrounds, our specific mission is to empower stakeholders with objective, high-impact insights and novel self-service tools. We go beyond reporting \"what\" happened to provide a clear understanding of “why” results occur, enabling more informed decision-making across the organization. Collaboration is core to our success; we are currently building the next generation of intelligent, AI-enabled analytical and experimentation platforms. These tools provide partners in Styling, Client Support, Marketing, and Engineering with the specialized capabilities they need to solve the company’s most complex business problems.\n About the Role \n In this role, you will partner with Client Support and Styling stakeholders, providing the analytical and technical expertise needed to turn data into actionable business strategy. You will design, execute, and analyze experiments and observational studies that uncover key insights for the company.\n A core focus of this position is providing training and guidance on self-service tools and platforms, ensuring partners can confidently navigate dashboards and reports to inform their workflows. We are looking for a strong communicator with a rich analytical background. As part of a high-visibility team, you will support cross-company innovation in how we evaluate and use data, driving impactful projects from Day 1.\n You're excited about this opportunity because you will… \n \n Develop sophisticated statistical models that provide causal insights to solve complex, large-scale business challenges. \n Own and evolve analytical strategies, from defining success metrics to translating complex results into clear executive narratives.\n Mentor and guide other data scientists, raising the bar for modeling, experimentation, and engineering excellence across the team.\n Partner with Client Support, Styling, and Product teams to build reliable data products and self-service tools that empower stakeholders.\n Tackle ambiguous, high-impact problems, bringing structure and technical leadership to drive innovative solutions from inception to completion.\n Leverage rich, multi-modal datasets spanning client behavior and merchandise attributes to uncover insights that power the next generation of styling decisions.\n \n We’re excited about you because… \n \n You have 2+ years of experience in a data science role, ideally within the e-commerce or retail industry.\n You hold a Bachelors or Masters degree in Statistics, Data Science, Computer Science, or a related quantitative field. \n You are proficient in Python or R and have experience writing SQL in collaborative, production-oriented environments.\n You are a strong communicator who can simplify complex technical concepts to drive alignment and action with business partners.\n You know how to leverage AI tools to streamline day-to-day tasks like testing and problem-solving, actively documenting effective prompts and sharing learnings to build scalable, repeatable workflows.\n You thrive in ambiguity, with a proven ability to own and drive projects from initial concept to delivery.\n You have a solid foundation in experimentation and causal inference, with the ability to link model performance directly to business outcomes.\n You are curious, pragmatic, and motivated to continuously raise the bar for technical excellence for yourself and your team.\n \n Why you'll love working at Stitch Fix... \n \n We are a group of bright, kind people who are motivated by challenge. We value integrity, innovation and trust. You’ll bring these characteristics to life in everything you do at Stitch Fix.\n We cultivate a community of diverse perspectives— all voices are heard and valued.\n We are an innovative company and leverage our strengths in fashion and tech to disrupt the future of retail. \n We win as a team, commit to our work, and ","salary_min":112500,"salary_max":144000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"junior","tags":["healthcare","payments","generative-ai","data-science"],"apply_url":"https://www.stitchfix.com/careers/jobs?gh_jid=7906045\u0026gh_jid=7906045","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-13T16:08:37Z","expires_at":"2026-06-29T14:18:30.559783Z","created_at":"2026-05-14T14:19:32.670314Z","updated_at":"2026-05-30T14:18:30.668291Z","company_name":"Stitch Fix","company_slug":"stitch-fix","company_logo_url":"https://www.google.com/s2/favicons?domain=stitchfix.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4da9ddfa-63f4-410c-a728-67df360aad68"},{"id":"47e10cfc-2765-44b7-b879-457d27bc5ebc","company_id":"286f7739-be56-491a-bcc7-de1df064fcd4","title":"Senior Data Scientist","slug":"senior-data-scientist-e5e44174","description":"Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com .\n As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do.\n Amplitude’s Commitment to Diversity Equity \u0026 Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive.\n About The Role \u0026 Team \n We’re looking for a Data Scientist to join the Experiment team within Amplitude. You will be part of a passionate group of product managers, engineers and designers who are working to help modern businesses transform their products through data and experimentation. As a Data Scientist, you have a unique opportunity to deeply influence the product with your knowledge and views on advanced statistical methodologies and customers who are looking to learn from an expert on experimentation best practice.  \n Join Amplitude and play a crucial role in shaping the future of experimentation and digital analytics. If you’re driven by innovation, strategic impact, and customer success, we’d love to hear from you!\n Our ambitious machine learning for experimentation agenda includes but is not limited to: \n \n Causal effects modeling or heterogeneous treatment effects analysis\n Analyzing experiments that have social network effects (ex: difference in differences, Switchback, Synthetic Control)\n Time Series modeling\n Bayesian hypothesis testing\n Understanding how teams run experiments\n B2B Experimentation\n Innovating and implementing machine learning and data mining algorithms on distributed platforms to solve real-world product analytics and user behavior modeling problems. \n \n   You'll be a great addition to the team if you have: \n \n A masters or Ph.D. degree in computer science, mathematics or related areas with extensive research/project experience in data science, experimentation, digital product optimization, math, statistics, etc. \n Have built and extensively used data pipelines in a variety of data warehouse environments.\n Proficiency with Python and SQL\n In-depth experience with Spark/Hadoop\n Has 2+ years of experience working as a Data Scientist in the past and is familiar with the Experimentation space, including hands-on experience using experimentation products\n Are interested and comfortable communicating with customers as a trusted advisor\n \n Our values:\n At Amplitude, our values guide how we show up for one another and for our customers:\n \n Humility: We operate from a place of empathy and openness, seeking to understand many points of view.\n Ownership: We take the initiative to solve problems that drive our shared company success.\n Growth Mindset: We’re tenacious in the face of challenges and seek feedback in order to grow ourselves and others.\n Customer Centricity: We put the customer at the center of everything we do and are deeply committed to their success.\n \n We care about the well-being of our team: We offer competitive pay and benefits packages that reflect our commitment to the health and well-being of our Ampliteers.\n Some of our benefit programs include:\n \n Excellent ​M​edical, ​D​ental and ​V​ision insurance coverages, with 100% employer-paid premiums for employee Medical, ​Dental,​ ​​​​​​​​Vision on select plans\n 401(k) retirement plan with an employer match of up to 1% of your eligible pay each pay period up to $2,000 annually\n Flexible time off, ​p​aid holidays, and more\n Generous stipends to spend on what matters most to you, whether that’s wellness (monthly), commuter transit/parking (monthly), learning and development (quarterly), new hire home office equipment, and much more\n Excellent Parental benefits including​:​ 12 weeks of Paid Parental Leave, Carrot Fertility Benefits/Adoption/Surrogacy support, Back-up Child Care support\n Mental health and wellness benefits including no cost employee access to Modern Health coaching \u0026 therapy sessions\n Employee Stock Purchase Program​ (ESPP)\n \n Other fun facts about Amplitude:  \n \n Our customers love us! They've said we're the #1 product analytics solution for 23 quarters in a row on G2.\n We care a lot about product innovation. We've made significan","salary_min":190000,"salary_max":286000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["payments","data-pipeline","fine-tuning","agents","data-science"],"apply_url":"https://job-boards.greenhouse.io/amplitude/jobs/8541697002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-08T19:31:52Z","expires_at":"2026-06-29T14:18:29.630316Z","created_at":"2026-05-10T14:20:20.413141Z","updated_at":"2026-05-30T14:18:29.750907Z","company_name":"Amplitude","company_slug":"amplitude","company_logo_url":"https://www.google.com/s2/favicons?domain=amplitude.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/47e10cfc-2765-44b7-b879-457d27bc5ebc"},{"id":"f8473e70-d698-4d8a-8e2b-7201b8cca131","company_id":"a0000000-0000-0000-0000-000000000001","title":"Data Scientist, Supply","slug":"data-scientist-supply-6a012908","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n Anthropic is compute-constrained, and how we allocate that compute is one of the highest-leverage decisions we make as a company. Today, those allocation choices are only loosely tied to the user outcomes we ultimately care about — retention, lifetime value, and the experience of people relying on Claude. You will change that.\n As a hands-on technical IC on the Supply pillar of our Data Science \u0026 Analytics team, you'll sit alongside the infrastructure engineers who run our compute and help decide how our scarcest resource gets used. You'll design and run the analyses, observational and synthetic experiments, and optimization frameworks that turn opaque supply decisions into shared, measurable understanding across the company. Your work will directly shape how frontier AI reaches the world at scale, and your findings will go in front of senior leadership, including our CTO and his staff.\n This role is a fit for someone who thinks natively in terms of constrained allocation and queueing, who enjoys getting close to the system rather than analyzing it from a distance, and who wants their analyses to translate into operational changes that ship.\n Responsibilities:\n \n Build and run testing frameworks — observational and synthetic — to quantify how different inputs affect compute allocation outcomes\n Connect compute allocation decisions to downstream user outcomes (retention, LTV, revenue) so we stop optimizing in a vacuum\n Partner closely with infrastructure engineers, product, and research to instrument the system, measure what matters, and ship operational changes\n Develop the metric hierarchies, dashboards, and reporting that turn supply decisions into shared understanding across the company\n Contribute analyses and recommendations to executive forums, and co-author the supply narrative the team takes to the CTO and his staff\n Measure and improve how AI affects developer productivity inside Anthropic\n \n You may be a good fit if you have:\n \n Strong technical IC background in data science, analytics, or operations research\n Operations research foundation — you think natively in terms of optimization, constrained allocation, and queueing\n Deep proficiency with Python, SQL, and data visualization tools\n Track record of owning analyses end-to-end and communicating results clearly to engineering and product leadership\n Direct experience working closely with engineering teams on production systems\n A passion for Anthropic's mission of building helpful, honest, and harmless AI\n \n Strong candidates may have: \n \n 6+ years of technical IC experience in data science, analytics, or operations research; 8+ years for candidates targeting a Staff-level scope\n Experience with highly complex systems with many interacting components (ad networks, payment processing, marketplace matching, routing, etc.)\n Experience with causal inference methods applied to operational decisions (synthetic controls, geo-experiments, switchbacks)\n Experience contributing to or designing experimentation platforms, not just using them\n Exposure to AI/ML products, large language models, or large-scale inference systems\n Track record of setting technical direction across multiple workstreams or mentoring senior ICs without formal management responsibility\n \n Deadline to apply: None. Applications are accepted on a rolling basis.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $275,000 — $370,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualif","salary_min":275000,"salary_max":370000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["payments","llm","alignment","data-science"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5212119008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-07T18:16:13Z","expires_at":"2026-06-29T14:00:13.49099Z","created_at":"2026-05-08T14:00:13.513051Z","updated_at":"2026-05-30T14:00:13.605199Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f8473e70-d698-4d8a-8e2b-7201b8cca131"},{"id":"44122084-724f-4c4e-9d68-1454bca70a3d","company_id":"a0000000-0000-0000-0000-000000000001","title":"Data Scientist, Developer Productivity","slug":"data-scientist-developer-productivity-c5623a98","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n As part of our growing Data Science and Analytics team, you'll play an instrumental role in Anthropic's mission of building safe and beneficial AI by driving data-informed decision making across the company. This role sits at the intersection of data science, developer experience, and AI tooling — and offers the unusual opportunity to study frontier AI usage from the inside, with the builders themselves as your users.\n You'll define how Anthropic understands and improves developer productivity — both through classic software engineering effectiveness measures and through the emerging challenge of understanding AI-augmented development workflows. You'll own the quantitative foundation for how Anthropic's engineers build: what slows them down, what accelerates them, where tooling investments pay off, and how AI-assisted development is changing the shape of engineering work. Your analyses will directly inform infrastructure priorities, tooling roadmaps, and how we think about scaling engineering output as Anthropic grows.\n You've worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale.\n Key responsibilities\n \n Define key metrics, build measurement frameworks, and maintain core reporting to evaluate developer productivity and engineering effectiveness\n Deep dive into product and user data to derive actionable insights, size opportunities, and influence roadmaps through clear recommendations\n Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to make actionable recommendations\n Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions\n Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes\n Present complex analyses and recommendations to both technical and non-technical stakeholders\n Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration as our products grow\n \n Minimum qualifications\n \n Working expertise with Python and SQL\n Working expertise with data visualization tools\n Hands-on experience with experimental design, causal inference, statistical modeling, and A/B testing frameworks\n Strong written communication and presentation skills\n Track record of translating complex data into clear, actionable insights for both technical and business stakeholders\n \n Preferred qualifications\n \n 7+ years of experience in data science or analytics roles\n Direct experience working with developer productivity, infrastructure, performance, or platform teams in rapidly scaling environments\n Deep understanding of distributed systems, cloud infrastructure, and performance engineering, with experience analyzing large-scale system metrics\n Experience applying experimental design and causal inference methods in high-scale technical environments\n Comfort with ambiguity and a track record of creating clarity and driving progress in fast-moving environments\n Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem\n Passion for Anthropic's mission of building helpful, honest, and harmless AI\n \n Deadline to apply: None. Applications are reviewed on a rolling basis.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $275,000 — $370,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every si","salary_min":275000,"salary_max":370000,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","alignment","cloud","llm","data-science"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5197529008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-06T06:22:41Z","expires_at":"2026-06-29T14:00:13.404715Z","created_at":"2026-05-06T14:00:19.175588Z","updated_at":"2026-05-30T14:00:13.51386Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/44122084-724f-4c4e-9d68-1454bca70a3d"},{"id":"9fc6dbf3-c1e8-4871-bb88-166ac8973560","company_id":"f1b3fbd3-ec84-4345-8bf8-4fd4394269dd","title":"Forward-Deployed Data Scientist II","slug":"forward-deployed-data-scientist-ii-2f45c691","description":"At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.\n We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.\n To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.\n Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.\n If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.\n WHAT YOU'LL DO \n As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:\n \n Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration\n Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components\n Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms\n Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise\n Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success\n \n WHO YOU ARE \n \n Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred\n Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred\n Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment\n Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions\n Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms\n Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value\n Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions\n Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow\n Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences\n \n For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company. \n #LI-Hybrid\n \n WHAT WE OFFER \n Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here . More details on benefits plans will be provided if you receive an offer of employment. \n From offering comprehensive benefits to fostering hybrid ways of working, we’ve got you covered so you can prioritize work-life harmony. Braze offers benefits such as:\n \n Competitive compensation that may include equity\n Retirement and Employee Stock Purchase Plans\n Flexible paid time off\n Comprehensive benefit plans covering medical, dental, vision, life, and disability\n Family services that include fertility benefits and equal paid parental leave\n Professional developme","salary_min":109000,"salary_max":183000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","tensorflow","mlops","reinforcement-learning","data-pipeline","data-science"],"apply_url":"https://boards.greenhouse.io/braze/jobs/7871576?gh_jid=7871576","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-04-30T17:00:12Z","expires_at":"2026-06-29T14:18:15.020823Z","created_at":"2026-05-06T14:25:11.823682Z","updated_at":"2026-05-30T14:18:15.133368Z","company_name":"Braze","company_slug":"braze","company_logo_url":"https://www.google.com/s2/favicons?domain=braze.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9fc6dbf3-c1e8-4871-bb88-166ac8973560"},{"id":"174ff47e-d04e-45e9-8f5b-a27903492b92","company_id":"f1b3fbd3-ec84-4345-8bf8-4fd4394269dd","title":"Forward-Deployed Data Scientist II","slug":"forward-deployed-data-scientist-ii-3034f608","description":"At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.\n We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.\n To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.\n Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.\n If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.\n WHAT YOU'LL DO \n As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:\n \n Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration\n Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components\n Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms\n Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise\n Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success\n \n WHO YOU ARE \n \n Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred\n Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred\n Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment\n Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions\n Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms\n Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value\n Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions\n Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow\n Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences\n \n For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company. \n #LI-Hybrid\n \n WHAT WE OFFER \n Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here . More details on benefits plans will be provided if you receive an offer of employment. \n From offering comprehensive benefits to fostering hybrid ways of working, we’ve got you covered so you can prioritize work-life harmony. Braze offers benefits such as:\n \n Competitive compensation that may include equity\n Retirement and Employee Stock Purchase Plans\n Flexible paid time off\n Comprehensive benefit plans covering medical, dental, vision, life, and disability\n Family services that include fertility benefits and equal paid parental leave\n Professional developme","salary_min":109000,"salary_max":183000,"location":"Chicago, IL","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","reinforcement-learning","mlops","agents","tensorflow","data-science"],"apply_url":"https://boards.greenhouse.io/braze/jobs/7871575?gh_jid=7871575","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-04-30T17:00:11Z","expires_at":"2026-06-29T14:18:15.101227Z","created_at":"2026-05-06T14:25:12.363971Z","updated_at":"2026-05-30T14:18:15.214296Z","company_name":"Braze","company_slug":"braze","company_logo_url":"https://www.google.com/s2/favicons?domain=braze.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/174ff47e-d04e-45e9-8f5b-a27903492b92"}],"page":1,"per_page":20,"total":414,"total_pages":21}